Abstract
ormance is a complex multifactorial phenomenon, therefore several variables should be considered to provide an accurate prediction of time in races. However, physiological variables have usually been used as the main predictors, ignoring the predictive potential of other factors such as psychological variables. The main aim of this study was to provide an equation for predicting performance at 10K, using both physiological and psychological factors as explanatory variables. 13 male runners participated in the study (weight 68.06 ± 18.73 kg; height 174.31 ± 5.39 cm; age 39.5 ± 8.5 years; 57.34 ± 5.03 ml - kg -min VO2MAX). A multiple regression model was established using a stepwise regression approach based on Ordinary Least Squares (OLS). After check possible collinearities, results showed as better predictors of the time at 10K event: VVO2MAX (β=-1.03), Arousal (β=0.17) and Isolation (β=0.19). The resulting regression showed a coefficient of determination (R 2 ) of 0.98 and RMSE= 50.30 s. VVO2MAX was the best predictor of the 10K performance. However, psychological factors, such as Arousal and Isolation, explain the addition variance. A higher VVO2MAX, a lower Arousal and a higher Isolation might allow better athletic performance in the 10K race. Keywords: Running; modelling; VO2MAX; isolation; activation; psychology. Resumen: El rendimiento en los eventos resistencia es un fenómeno multifactorial complejo, por lo que deben considerarse diversas variables para proporcionar una predicción precisa del tiempo en las carreras. Hasta la fecha se han utilizado las variables fisiológicas como principales predictores, ignorando el potencial predictivo de otros factores como las variables psicológicas. El objetivo principal de este estudio fue proporcionar una ecuación para predecir el rendimiento en 10K, utilizando tanto factores fisiológicos como psicológicos
que deben considerarse diversas variables para proporcionar una predicción precisa del tiempo en las carreras. Hasta la fecha se han utilizado las variables fisiológicas como principales predictores, ignorando el potencial predictivo de otros factores como las variables psicológicas. El objetivo principal de este estudio fue proporcionar una ecuación para predecir el rendimiento en 10K, utilizando tanto factores fisiológicos como psicológicos como variables explicativas. Participaron en el estudio 13 corredores varones (Peso 68,06 ± 18,73 kg; Altura 174,31 ± 5,39 cm; edad 39,5 ± 8,5 años; 57,34 ± 5,03 ml - kg -min VO2MAX). Se estableció un modelo de regresión múltiple utilizando un enfoque de regresión por pasos basado en mínimos cuadrados ordinarios. Tras comprobar las posibles colinealidades, los resultados mostraron el VVO2MAX (β=-1,03), Activación (β=0,17) y Aislamiento (β=0,19), como mejores predictores del tiempo en la prueba de 10K. La regresión resultante mostró un coeficiente de determinación (R 2 ) de 0,98 y RMSE= 50,30 s. VVO2MAX fue el mejor predictor del rendimiento en 10K. Sin embargo, los factores psicológicos, como la activación y el aislamiento, explican la varianza adicional. Un mayor VVO2MAX, una menor activación y un mayor aislamiento podrían permitir un mejor rendimiento en la carrera de 10K. Palabras clave: Carrera; modelización; VO2MAX; aislamiento; activación; psicología. Fecha recepción: 29-04-24. Fecha de aceptación: 25-09-24 Iker Muñoz Pérez iker.munoz@deusto.es Introduction Endurance is defined as the capacity to withstand psychophysical fatigue for a certain period of time (Weineck, 2005). What is more, in endurance sports like in running races, participants need to complete a set distance in the shortest time possible , which is perceived as performance (Ganio et al., 2009; Martínez-Sanz et al., 2020). Sports performance is influenced by the interrelation of different physiological and psychological factors. In this sense, both the functional state and the physical conditions in addition to other external factors influence and determine the competitive results (Clemente-Suárez et al., 2021). In this sense, physiological factors are the most extensively studied variables associated with performance in endurance sports (Coyle, 1999). These include the following variables: running economy (understood as how efficiently a runner uses oxygen while running at
the functional state and the physical conditions in addition to other external factors influence and determine the competitive results (Clemente-Suárez et al., 2021). In this sense, physiological factors are the most extensively studied variables associated with performance in endurance sports (Coyle, 1999). These include the following variables: running economy (understood as how efficiently a runner uses oxygen while running at a submaximal speed), lactate/ventilatory thresholds (defined as physiological landmarks representing the shift from primarily aerobic to anaerobic metabolism) , and maximum oxygen uptake (VO2MAX) or VVO2MAX (Tegenge & Melkamu, 2024) representing the minimum velocity needed to elicit VO2MAX (Jones & Carter, 2000). ). Other authors also propose variables such as Critical Speed, the fractional use of VO2MAX, the lactate turning point or the resilience (Alvero-Cruz et al., 2020; Jones et al., 2023). However, VO2MAX and VVO2MAX are among the most frequently measured in sports sciences (Levine, 2008). VO2MAX has been used to partially explain the performance of the cardiovascular system (Bassett & Howley, 2000; Joyner & Dominelli, 2021), establishing a superior limit of energy production in prolonged work. In addition, this factor explains a very high percentage of endurance performance (Evans et al., 1995; McLaughlin et al., 2010), although not all variance. Attending to 10K races, several studies have shown a close relationship between performance at this distance and VO2MAX (Evans et al., 1995; Fay et al., 1989; Kumagai et al., 1982; Meireles et al., 2012; Morgan et al., 1989; Tanaka et al., 1985) although it varies according to the level of the athletes. In this regard, Abad et al. (2016) indicated that there was no relationship between VO2MAX and 10K performance. Additionally, VVO2MAX explains a high percentage of performance, and seems to be decisive when subjects are paired at the same VO2MAX (Meireles et al., 2012; Morgan et al., 1989). Thus, when both subjects have the same values of maximal oxygen uptake, the athlete who displays higher speed at VO2MAX achieves better results (Meireles et al., 2012). A study conducted by McLaughlin et al. (2010) with 17 well-trained runners concluded that the best
the same VO2MAX (Meireles et al., 2012; Morgan et al., 1989). Thus, when both subjects have the same values of maximal oxygen uptake, the athlete who displays higher speed at VO2MAX achieves better results (Meireles et al., 2012). A study conducted by McLaughlin et al. (2010) with 17 well-trained runners concluded that the best
2024, Retos, 61, 774-784 © Copyright: Federación Española de Asociaciones de Docentes de Educación Física (FEADEF) ISSN: Edición impresa: 1579-1726. Edición Web: 1988-2041 (https://recyt.fecyt.es/index.php/retos/index) -775- Retos, número 61, 2024 (diciembre) variable predicting the performance of a 16K endurance test was VVO2MAX, compared to VO2MAX, or to the percentage of VO2MAX at the second lactate threshold. Regarding the performance of the 10K race, a relationship was also been found between the time achieved and the minimum speed reached by VO2MAX (VVO2MAX) (Meireles et al., 2012, Morgan et al., 1989). A study by Meireles et al. (2012), VVO2MAX also predicted the performance to a large extent, although it was slightly lower than VO2MAX. Thus, both physiological parameters (VO2MAX and VVO2MAX) are important for endurance performance. In addition to the athlete's physiological capabilities, the psychological dimension, such as motivation, should also be considered to improve the explanation of performance (Röthlin et al., 2022; Yendrizal et al., 2024). Previous studies have highlighted that physiological factors do not contribute to explain all variance when endurance performance is predicted when endurance performance is predicted (Evans et al., 1995; McCormick et al., 2015; Keogh et al., 2019; Alvero-Cruz et al., 2020). Therefore, the psychobiological endurance model might better explain the influence of these variables on sports performance than one of them alone (Röthlin et al., 2022). Thus, psychological factors influence endurance performance, according to the psycho-biological model of endurance (Marcora, 2008), an effort-based decision-making model based on motivational intensity theory. The model suggests that perception of effort and prospective incentive are the main factors influencing conscious pace management. Considering this model, athletes will stop their endurance activity when the effort required by the work exceeds the highest effort the individual is willing to make and they find it impossible to continue the activity (Marcora & Staiano, 2010). In this context, the main factor limiting endurance performance is the perception of individual effort (Blanchfield et al., 2014). Consequently, any physiological or psychological factor that influences this perception of effort may affect endurance performance (Marcora et al., 2008). Thus, factors such as motivation, or use of mental techniques such
it impossible to continue the activity (Marcora & Staiano, 2010). In this context, the main factor limiting endurance performance is the perception of individual effort (Blanchfield et al., 2014). Consequently, any physiological or psychological factor that influences this perception of effort may affect endurance performance (Marcora et al., 2008). Thus, factors such as motivation, or use of mental techniques such as self-talk, goal setting, arousal or imagery, could affect endurance performance (Gould & Udry, 1994; McCormick et al., 2015, Taylor et al., 2020; Wallace et al., 2017; Kurniawan et al., 2023). The first factors that could influence endurance performance are mental techniques, including self-talk, arousal regulation, imagery, and goal-setting. In this regard, self-talk refers to what the athlete says to himself/herself loudly, silently, automatically, or strategically, to correct, stimulate, or evaluate the action (Hatzigeorgiadis et al., 2011), and is one of the most practical strategies for improving athletes’ performance. Moreover, it also helps athletes to increase their motivation or focus on sports tasks (Van Raalte et al., 2016). The use of motivational self-talk improves time-trial performance during cycling, displaying higher levels of power (Barwood et al., 2015). Wallace et al. (2017), conducted a motivational self-talk intervention with cyclists for two weeks showing increase on performance during a maximal cycle ergometer test in heat conditions (35ºC). These authors concluded that motivational self-talk not only increased performance, but also helped to tolerate heat much better. Finally, it can be stated that self-talk can be a powerful tool to improve the confidence, motivation and performance of athletes, especially positive or motivational self-talk (Blanchfield et al., 2014; Winberg et al., 1984; Basset et al., 2022). Arousal is another psychological factor that is related to sports performance. This factor is defined as a cognitive and somatic reaction to an internal or external stimulus (Birrer & Morgan, 2010). What is more, it refers to the overall combination of physical and mental level of activity that a person feels, which can range from being in a deep sleep to feeling extremely excited (Wesson et al., 2000). There is an optimal state of arousal for each athlete to
somatic reaction to an internal or external stimulus (Birrer & Morgan, 2010). What is more, it refers to the overall combination of physical and mental level of activity that a person feels, which can range from being in a deep sleep to feeling extremely excited (Wesson et al., 2000). There is an optimal state of arousal for each athlete to reach the maximum level of performance (Birrer & Morgan, 2010). However, this differs according to variables such as situational factors, a combination of cognitive and affective sensations (Hardy et al., 1996), the demands of the sport, and personal preferences (Hanin, 2000). Scientific evidence indicates that techniques that regulate arousal serve to manage stress, arrive at competition in an optimal mental state, and thus, increase performance (Gould & Udry, 1994). However, contrary to this evidence, in a recent study by Röthlin et al. (2022) in which the influence of different psychological and physiological variables on performance was analyzed, arousal was not related to improvement in performance. There is still a need for research on the materialization of this regulation "when", "with whom" and "how". In turn, imagery or visualization, which is referred to as the creation or recreation of experiences created from the subject's memories or information in memory, might influence athletes’ performance (Simonsmeier et al., 2021). Specifically, in endurance sports, several studies have shown that using visualization technique training improves performance in swimmers (Post et al., 2012) and runners (Spino & Straub, 2014). Another widespread mental technique used by athletes is goal setting. Locke and Latham (2002) developed the theory of this psychological factor. Through this theory, the authors explained that objectives directly influence the individual's attitude. Athletes use process and/or performance goals to focus on the athletic task, among others (Weinberg & Butt, 2014). In this study, which was conducted with amateur marathoners, experienced runners were asked about their target running time while other experienced runners were not and first ones ran faster than unasked marathoners (Sackett et al., 2014). This made their goals more ambitious and improved their performance. On the other hand, in a study that was
others (Weinberg & Butt, 2014). In this study, which was conducted with amateur marathoners, experienced runners were asked about their target running time while other experienced runners were not and first ones ran faster than unasked marathoners (Sackett et al., 2014). This made their goals more ambitious and improved their performance. On the other hand, in a study that was conducted with five university students aged 18-28 years, it helped them to increase the distance they ran per week, i.e. to set short and long term goals, they increased their weekly running time (Wack et al., 2014). Regard to psychological variables,
2024, Retos, 61, 774-784 © Copyright: Federación Española de Asociaciones de Docentes de Educación Física (FEADEF) ISSN: Edición impresa: 1579-1726. Edición Web: 1988-2041 (https://recyt.fecyt.es/index.php/retos/index) -776- Retos, número 61, 2024 (diciembre) motivation is another important factor that might affect endurance performance. Motivation refers to the process of initiating and maintaining goal-oriented activities (Cook & Artino, 2016). Besides, motivation refers to the direction and the intensity of the effort that a person does (Sage, 1977); direction of effort refers to what an individual is attracted to (i.e. winning a race) and intensity refers to how much effort a person is disposed to do to achieve a goal (Morgan and Sproule, 2012). Vallerand and Thill (1993) analyzed motivation in the sports environment and defined it as any internal and external force that gives initiation, direction, intensity, and persistence to both an individual attitude and an action. Among university athletes, autonomous or intrinsic motivation showed a close relationship with perception, sport satisfaction or sport performance to achieve goals. Therefore, this variable seems to be a determinant in different sports fields, not only in high performance (Vallerand & Till, 1993). In addition, motivational patterns improve performance in middle- distance running (Donohue et al., 2006; Miller & Donohue, 2003) and appear to be related to athletic ability in intermittent sports (Zuber & Conzelmann, 2014). Finally, self-compassion is one of the most important psychological determinants of success that athletes can aspire to and that athletes perceive as limiting or necessary when working towards their goals or expectations, although the relationship between this psychological variable and sports performance is complex (Adam et al., 2021). Self-compassion is understood as the recognition of one's own suffering and the desire to alleviate it, offering protection, in this case to the athlete, from maladaptive psychological experiences in sport (Cormier et al., 2023). That is, self-compassion would include being kind and understanding with oneself, as well as the desire to achieve one's own well-being and not adopting a self-critical stance with one's perceived shortcomings and weaknesses in oneself. (Röthlin et al., 2019). In terms of sport performance, in major competitions, such as territorial
from maladaptive psychological experiences in sport (Cormier et al., 2023). That is, self-compassion would include being kind and understanding with oneself, as well as the desire to achieve one's own well-being and not adopting a self-critical stance with one's perceived shortcomings and weaknesses in oneself. (Röthlin et al., 2019). In terms of sport performance, in major competitions, such as territorial or international competitions, women, for example, use self- compassion to foster perceptions of performance and well- being when training and competing (Killham et al., 2018). Some athletes recognise that self-compassion reinforces perseverance to overcome difficulties, which, as discussed above, might improve performance through psychological pathway (Ferguson et al., 2014). In contrast, in a study conducted with subelite cyclists, there was no direct relationship with endurance performance (Röthlin et al., 2022). Hence, although physiological factors such as VO2MAX, VVO2MAX or lactate threshold have been studied extensively (Jones & Carter, 2000; Bassett & Howley, 2000; Joyner & Coyle, 2008), psychological factors have received less scientific interest. For this reason, even athletes recognize that psychological factors influence their performance, attempts to predict it considering both dimensions are limited in scientific literature (Röthlin et al., 2022). However, these have often been investigated independently of physiological factors (Morgan et al., 1989; McCormick et al., 2015; Barwood et al., 2015; Billat et al., 2001; Jones, 2006; Jones et al., 2021). Consequently, the main aim of this study was to analyze whether psychological factors influence performance or contribute to higher performance in 10K race, taking into account individual physiological factors. To conduct this study, the work of (Röthlin et al., 2022) was used as a reference. Finally, our hypothesis was that the inclusion of psychological and physiological factors would significantly improve the predictive accuracy of the regression model compared with the use of physiological variables alone. Materials and methods Design and Participants The present study followed a retrospective design. The inclusion criteria for this study were as follows: (I) training and competing experience as an athlete (> 5 years practicing this sport), (II) running more than 3 days a week for 45 min, and (III) not being
model compared with the use of physiological variables alone. Materials and methods Design and Participants The present study followed a retrospective design. The inclusion criteria for this study were as follows: (I) training and competing experience as an athlete (> 5 years practicing this sport), (II) running more than 3 days a week for 45 min, and (III) not being injured at the time of the study. Once the inclusion criteria were considered, 13 male runners participated in the study (weight 68.06 ± 18.73 kg; height 174.31 ± 5.39 cm; age 39.5 ± 8.5 years; 52.18 ± 16.22 ml - kg - min VO2MAX). All participants provided a medical check-up and signed an informed consent form before participating in the study. This study was approved by the Ethics Committee of the Department of Physical Activity and Sport Sciences (Reference: ETK-52/21-22) and was conducted in accordance with the Declaration of Helsinki. The performance of the samples was classified according to the criteria of McKay et al. (2022). To differentiate trained/developed and national-level athletes according to this classification, the minimum marks established for national championships in 2022 were consulted (Real Federación Española de Atletismo, 2023). In this study, 12 runners in the sample were trained/developed, and one runner was a national-level runner. Measures Data collection took place over two days, the first day was conducted in the laboratory, where a graded exercise protocol (GXP) was performed. The second day was the race day (10K Villa de Laredo), one of the fastest races at both national and international level, where the second fastest World Time has been made (World Athletics, 2023). On the morning of the race day, participants completed a questionnaire to measure psychological factors, and in the afternoon, they completed the race. The race time was collected as a performance indicator. Running time in the previously mentioned race was taken as the dependent variable, while psychological variables, VO2MAX and VVO2MAX were independent variables. Physiological measurements were carried out 6 days before or 10 days after the race, minimizing the interference effect between them. Subjects were advised
race. The race time was collected as a performance indicator. Running time in the previously mentioned race was taken as the dependent variable, while psychological variables, VO2MAX and VVO2MAX were independent variables. Physiological measurements were carried out 6 days before or 10 days after the race, minimizing the interference effect between them. Subjects were advised
Description
The study analyzes the impact of psychological and physiological factors on 10K race performance.